Dynamic synthesis of the alpha-type stirling engine based on reducing the output velocity fluctuations using Metaheuristic algorithms

A. Rahmati, S.M. Varedi-Koulaei, M.H. Ahmadi and H. Ahmadi

Energy, 2022, vol. 238, issue PB

Abstract: As an external combustion engine, the Stirling engine has low noise and can also easily use renewable and modern energies, such as solar energy. In this study, the dynamic synthesis of the alpha-type Stirling engine will be discussed. By combining the Stirling engine's thermodynamic and dynamic models, it is possible to predict the thermal efficiency, output power, and output velocity of the engine. It can be seen that the output angular velocity of the engine has some undesirable fluctuations. The main goal here is to reduce or eliminate the oscillatory behavior of the output angular velocity by optimizing the links' lengths and their mass distribution in the engine's mechanism. Three optimization methods, namely the Genetic algorithm, the Particle swarm optimization, and the Imperialist competition algorithm, are used for searching the optimum design based on minimizing the output velocity fluctuations. Results show that if the flywheel's mass moment of inertia is fixed, the angular velocity fluctuations have decreased by 24.18 %, 19.20 %, and 24.48 % using GA, PSO, ICA, respectively. Moreover, at the same time, the efficiency has been improved by 38 % approximately. For the best design in this case, which was extracted from Imperialist competition algorithm, the fluctuation has reduced to 133.72 rpm, while the average output velocity is 2620 rpm. Furthermore, as a second case, increasing the flywheel's mass moment of inertia directly affects reducing the velocity fluctuations.

Keywords: Stirling engine; Dynamic synthesis; Velocity fluctuations; Evolutionary algorithms (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544221019344
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:238:y:2022:i:pb:s0360544221019344

DOI: 10.1016/j.energy.2021.121686

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().